CROSS-REFERENCE TO RELATED APPLICATION
This application claims the benefit of U.S. Provisional Patent Application 61/495,584 filed Jun. 10, 2011 entitled “Prospect Assessment and Play Chance Mapping Tools,” the entirety of which is incorporated by reference herein.
- Top of Page
A prospect includes an area of exploration in which hydrocarbons have been predicted to exist in economic quantity. A prospect may include an anomaly, such as a geologic structure or a seismic amplitude anomaly that is recommended by explorationists for drilling a well. Justification for drilling a prospect is made by assembling evidence for an active petroleum system, or reasonable probability of encountering reservoir-quality rock, a trap of sufficient size, adequate sealing rock, and appropriate conditions for the generation and migration of hydrocarbons to fill the trap. A single drilling location is also called a prospect, but the term is generally used in the context of exploration: exploration prospect assessment (EPA), hereinafter referred to as Prospect Assessment (PA).
A group of prospects of a similar nature constitutes a play. Thus, a play is a region in which hydrocarbon accumulations or prospects of a given type may occur: a conceptual model for a style of hydrocarbon accumulation used by explorationists to develop prospects in a basin, region, or trend and used by development personnel to continue exploiting a given trend. A play (or a group of interrelated plays) may occur in a single petroleum system.
Common Risk Segment Mapping (CRSM) is an exploration method to define areas of low exploration risk. Certain companies employ some method of play fairway mapping and common risk mapping. These may be used to define play Chance of Success (play COS) at the play level and local prospect Chance of Success (prospect COS) at the prospect level. “Traffic light” maps of red, yellow and green for high, moderate and low risk areas are examples of displays in the industry. CRSM maps that combine the geological elements that determine the Chance of Success of plays and prospects may be further combined with maps that delineate other risk elements that affect the overall prospectivity in an area, for example, distance from shore, water depth, accessibility to acreage, and so forth.
Play-based exploration may have a different focus than prospect-based exploration. Beyond the traffic light maps, there may be maps that show shared/play-specific and local/prospect-specific probabilities. A problem with these conventional probability and Chance of Success maps, however, may be the relative complexity of arriving at the map itself, such that if a geological condition changes, or when the explorationist changes a hypothetical or a geological property underpinning the map, the map has to be reconfigured and recalculated, which may be a conventionally painstaking process.
Play fairway mapping, common risk mapping, and Chance of Success mapping conventionally depend on numerous complex processes. The shear amount of input data through which the user may need to sort can make map creation difficult and sometimes non-intuitive. Additionally, there may be a lack of information on how to accomplish the exploration workflows. Easy-to-use tools may be needed to give fast results and simplify the clutter of inputting data for the process of creating the Chance of Success maps and evaluating the results.
- Top of Page
Prospect assessment and play chance mapping tools are provided. For exploration prospect assessment of potential hydrocarbon resources in a play or a prospect, an example system provides dynamically linked, real time risk, chance of success, and chance of failure maps (“chance maps”), transformed in real time from the geological properties of one or more input geological maps, play fairway maps, or other input data. The geological maps and data input to the system are dynamically linked to the resulting output: chance maps, so that a change to a geologic parameter of an input map or input datum automatically updates the chance map(s) in real time or near real time. In an example implementation, user-instigated changes in an example user interface are also instantly reflected in the resulting chance map. The example user interface allows the user to create and specify a custom hierarchical matrix of risk maps, including specifying dynamically linked input maps and data, and the dynamic links themselves. The user can specify sub-maps and sub-matrices to construct the main risk matrix, selecting and dropping maps directly into the matrix. A customizable transform quickly converts geologic properties from the geologic domain to the chance domain. The user interface also enables the user to navigate geological maps, draw a polygon around areas of interest (AOI) or otherwise select areas on a geologic map. After selecting an area, the user may drag-and-drop geologic properties within the polygon directly into an uncertainty engine that maps risk by applying an equation or by building a distribution to map uncertainty in a manner that is automatically tied directly back to geologic reality. A merge tool can apply a customizable formula to perform a programmatic merge of multiple grids that are modeling multiple different geological interpretations of a prospect. The merge tool outputs a single chance of success value for multiple geologic property values at each grid node.
This summary section is not intended to give a full description of prospect assessment and play chance mapping tools, or to provide a comprehensive list of features and elements. A detailed description with example implementations follows.
BRIEF DESCRIPTION OF THE DRAWINGS
- Top of Page
FIG. 1 is a block diagram of an example system and environment for prospect assessment and play chance mapping tools.
FIG. 2 is a diagram of an example play chance matrix.
FIG. 3 is a diagram of an example transform table.
FIG. 4 is a diagram of an example property to chance of success map conversion via transform.
FIG. 5 is a diagram of an example process of selecting an area of a geological map to drag-and-drop property values into a distribution for creating a live chance of success map.
FIG. 6 is a flow diagram of an example process setting up a chance of failure map.
FIG. 7 is a diagram of an example histogram or distribution builder for creating a chance of failure map.
FIG. 8 is a diagram of an example merge process for generating a single chance of success value for a distribution of geologic values at each grid node of a grid that is modeling a play or prospect.
FIG. 9 is a flow diagram of an example process for inputting maps to generate a risk map.
FIG. 10 is a flow diagram of the example process in FIG. 9 with an uncertainty option.
FIG. 11 is a flow diagram of the example process in FIG. 10, with an auto update option.
FIG. 12 is a diagram of an example user interface for creating a chance map.
FIG. 13 is a diagram of an example user interface showing default templates.
FIG. 14 is a diagram of an example user interface showing icons or buttons for creating and linking input maps and risk maps.
FIG. 15 is a diagram of an example user interface showing creation of submaps during matrix and map creation.
FIG. 16 is a diagram of an example user interface showing matrix handling.
FIG. 17 is a diagram of an example user interface showing matrix creation.
FIG. 18 is a diagram of an example user interface showing value entering during matrix creation.
FIG. 19 is a diagram of an example user interface showing an option for loading a pre-made matrix.
FIG. 20 is a diagram of an example user interface showing how to input a play-fairway map 122.
FIG. 21 is a diagram of an example user interface showing input of a single value via typing or scaling on a visual slider.